Department of Aeronautics and Astronautics, Massachusetts Institute of Technology, Cambridge, MA 02139.
Department of Architecture, Massachusetts Institute of Technology, Cambridge, MA 02139.
Proc Natl Acad Sci U S A. 2024 Apr 30;121(18):e2215682121. doi: 10.1073/pnas.2215682121. Epub 2024 Apr 22.
Sustainability challenges related to food production arise from multiple nature-society interactions occurring over long time periods. Traditional methods of quantitative analysis do not represent long-term changes in the networks of system components, including institutions and knowledge that affect system behavior. Here, we develop an approach to study system structure and evolution by combining a qualitative framework that represents sustainability-relevant human, technological, and environmental components, and their interactions, mediated by knowledge and institutions, with network modeling that enables quantitative metrics. We use this approach to examine the water and food system in the Punjab province of the Indus River Basin in Pakistan, exploring how food production has been sustained, despite high population growth, periodic floods, and frequent political and economic disruptions. Using network models of five periods spanning 75 y (1947 to 2022), we examine how quantitative metrics of network structure relate to observed sustainability-relevant outcomes and how potential interventions in the system affect these quantitative metrics. We find that the persistent centrality of some and evolving centrality of other key nodes, coupled with the increasing number and length of pathways connecting them, are associated with sustaining food production in the system over time. Our assessment of potential interventions shows that regulating groundwater pumping and phasing out fossil fuels alters network pathways, and helps identify potential vulnerabilities for future food production.
与食物生产相关的可持续性挑战源于长时间内发生的多种自然-社会相互作用。传统的定量分析方法无法代表系统组件网络的长期变化,包括影响系统行为的制度和知识。在这里,我们通过结合定性框架和网络建模来研究系统结构和演变,定性框架代表了与可持续性相关的人类、技术和环境组成部分及其相互作用,这些组成部分通过知识和制度进行中介,而网络建模则可以实现定量指标。我们使用这种方法来研究巴基斯坦印度河流域旁遮普省的水和粮食系统,探讨尽管人口增长迅速、周期性洪水和频繁的政治经济动荡,粮食生产是如何得以维持的。我们使用跨越 75 年(1947 年至 2022 年)的五个时期的网络模型,研究网络结构的定量指标如何与观察到的可持续性结果相关,以及系统中的潜在干预措施如何影响这些定量指标。我们发现,一些关键节点的持久中心性和其他节点的不断演变的中心性,加上连接它们的路径数量和长度的增加,与该系统中随着时间的推移维持粮食生产有关。我们对潜在干预措施的评估表明,调节地下水抽取和逐步淘汰化石燃料可以改变网络路径,并有助于确定未来粮食生产的潜在脆弱性。